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New insights into urban functional zones with a specific focus on leisure is of great significance for human-oriented urban development. The spatiotemporal pattern of urban leisure functional zones (ULFZ) reflects to what extent human psychological needs are satisfied. This article aims to discern ULFZ and reveal their changing regularity based on the taxi trajectory data and points of interests (POIs) by the DBSCAN algorithm, latent dirichlet allocations (LDA) and spatial analytical techniques. Results are concluded as follows: 1) the spatial distribution of ULFZs are dynamic and imbalanced at various periods; 2) among urban leisure subfunctions, cultural function is severely weaker than entertaining, sportive, and tourist function; and 3) the changes in ULFZ are kind of consistent at multiple spatial scales. This research benefits the leisure-oriented urban planning.
Ying Jing; Junjiao Shu; Rushan Wang; Xiang Zhang. Tempo‐spatial variability of urban leisure functional zones: An analysis based on geo‐big data. Growth and Change 2021, 1 .
AMA StyleYing Jing, Junjiao Shu, Rushan Wang, Xiang Zhang. Tempo‐spatial variability of urban leisure functional zones: An analysis based on geo‐big data. Growth and Change. 2021; ():1.
Chicago/Turabian StyleYing Jing; Junjiao Shu; Rushan Wang; Xiang Zhang. 2021. "Tempo‐spatial variability of urban leisure functional zones: An analysis based on geo‐big data." Growth and Change , no. : 1.
This article presents how a generative adversarial network (GAN) can be employed to produce a generalised map that combines several cartographic themes in the dense context of urban areas. We use as input detailed buildings, roads, and rivers from topographic datasets produced by the French national mapping agency (IGN), and we expect as output of the GAN a legible map of these elements at a target scale of 1:50,000. This level of detail requires to reduce the amount of information while preserving patterns; covering dense inner cities block by a unique polygon is also necessary because these blocks cannot be represented with enlarged individual buildings. The target map has a style similar to the topographic map produced by IGN. This experiment succeeded in producing image tiles that look like legible maps. It also highlights the impact of data and representation choices on the quality of predicted images, and the challenge of learning geographic relationships.
A. Courtial; G. Touya; X. Zhang. GENERATIVE ADVERSARIAL NETWORKS TO GENERALISE URBAN AREAS IN TOPOGRAPHIC MAPS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2021, XLIII-B4-2, 15 -22.
AMA StyleA. Courtial, G. Touya, X. Zhang. GENERATIVE ADVERSARIAL NETWORKS TO GENERALISE URBAN AREAS IN TOPOGRAPHIC MAPS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2021; XLIII-B4-2 ():15-22.
Chicago/Turabian StyleA. Courtial; G. Touya; X. Zhang. 2021. "GENERATIVE ADVERSARIAL NETWORKS TO GENERALISE URBAN AREAS IN TOPOGRAPHIC MAPS." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2, no. : 15-22.
Crowd-sourced geographic information has great potential in scientific and public domains, and is recently under consideration by geospatial professionals as an alternative to traditional spatial data collection. The success, however, implies a need to build long-term reliance on the crowd-sourcing projects, and poses growing concern over the quality of the constantly evolving data. In general, we aim to develop an approach that uses geographic rules to identify inconsistent information in street networks without relying on external sources. This paper focuses on a more challenging sub-process that aims to identifying inconsistent information using the rule of symmetry. That is, information (e.g. name, class, speed limit, etc.) in parallel carriageways (e.g. divided highways) always constrains each other. The process starts with a clustering of related streets into well-defined or ambiguous situations using a DBSCAN-inspired technique; then two pairing strategies are designed for both situations. To address the challenging problem of pairing carriageways in ambiguous situations, three pairing algorithms (stroke-based, tree-based, and mixed) are devised based on the idea of using expanded ‘receptive field’ to disentangle the ambiguities; each has a focus on efficiency, effectiveness, or their tradeoff. Evaluating the algorithms against 7 selected datasets shows that all three algorithms reached satisfactory performance (F1-score > 92%) for ambiguous situations, and much higher accuracy for the whole datasets. Then, we applied our approach to over 40 datasets worldwide and detected inconsistencies (i.e. dissimilar values in paired carriageways) in crowd-sourced and authoritative street networks. We evaluate the identified inconsistencies, analyze the possibilities of our approach in suggesting corrections to problematic data, and discuss its effectiveness, issues, and future directions. We thereby demonstrate that the proposed approach is effective for quality assurance, and can be used to assure the quality of crowd-sourced and authoritative mapping projects during their evolution without relying on ground-truth.
Xiang Zhang; Tianfu Wang; Delin Jiao; Zhiying Zhou; Jianwei Yu; Xiao Cheng. Detecting inconsistent information in crowd-sourced street networks based on parallel carriageways identification and the rule of symmetry. ISPRS Journal of Photogrammetry and Remote Sensing 2021, 175, 386 -402.
AMA StyleXiang Zhang, Tianfu Wang, Delin Jiao, Zhiying Zhou, Jianwei Yu, Xiao Cheng. Detecting inconsistent information in crowd-sourced street networks based on parallel carriageways identification and the rule of symmetry. ISPRS Journal of Photogrammetry and Remote Sensing. 2021; 175 ():386-402.
Chicago/Turabian StyleXiang Zhang; Tianfu Wang; Delin Jiao; Zhiying Zhou; Jianwei Yu; Xiao Cheng. 2021. "Detecting inconsistent information in crowd-sourced street networks based on parallel carriageways identification and the rule of symmetry." ISPRS Journal of Photogrammetry and Remote Sensing 175, no. : 386-402.
Yingzhe Lei; Tinghua Ai; Xiang Zhang; Jingzhong Li. A parallel annotation placement method for dense point of interest labels using hexagonal grid. Cartography and Geographic Information Science 2020, 48, 95 -104.
AMA StyleYingzhe Lei, Tinghua Ai, Xiang Zhang, Jingzhong Li. A parallel annotation placement method for dense point of interest labels using hexagonal grid. Cartography and Geographic Information Science. 2020; 48 (2):95-104.
Chicago/Turabian StyleYingzhe Lei; Tinghua Ai; Xiang Zhang; Jingzhong Li. 2020. "A parallel annotation placement method for dense point of interest labels using hexagonal grid." Cartography and Geographic Information Science 48, no. 2: 95-104.
Among cartographic generalisation problems, the generalisation of sinuous bends in mountain roads has always been a popular one due to its difficulty. Recent research showed the potential of deep learning techniques to overcome some remaining research problems regarding the automation of cartographic generalisation. This paper explores this potential on the popular mountain road generalisation problem, which requires smoothing the road, enlarging the bend summits, and schematising the bend series by removing some of the bends. We modelled the mountain road generalisation as a deep learning problem by generating an image from input vector road data, and tried to generate it as an output of the model a new image of the generalised roads. Similarly to previous studies on building generalisation, we used a U-Net architecture to generate the generalised image from the ungeneralised image. The deep learning model was trained and evaluated on a dataset composed of roads in the Alps extracted from IGN (the French national mapping agency) maps at 1:250,000 (output) and 1:25,000 (input) scale. The results are encouraging as the output image looks like a generalised version of the roads and the accuracy of pixel segmentation is around 65%. The model learns how to smooth the output roads, and that it needs to displace and enlarge symbols but does not always correctly achieve these operations. This article shows the ability of deep learning to understand and manage the geographic information for generalisation, but also highlights challenges to come.
Azelle Courtial; Achraf El El Ayedi; Guillaume Touya; Xiang Zhang. Exploring the Potential of Deep Learning Segmentation for Mountain Roads Generalisation. ISPRS International Journal of Geo-Information 2020, 9, 338 .
AMA StyleAzelle Courtial, Achraf El El Ayedi, Guillaume Touya, Xiang Zhang. Exploring the Potential of Deep Learning Segmentation for Mountain Roads Generalisation. ISPRS International Journal of Geo-Information. 2020; 9 (5):338.
Chicago/Turabian StyleAzelle Courtial; Achraf El El Ayedi; Guillaume Touya; Xiang Zhang. 2020. "Exploring the Potential of Deep Learning Segmentation for Mountain Roads Generalisation." ISPRS International Journal of Geo-Information 9, no. 5: 338.
As a result of the increasing popularity of indoor activities, many facilities and services are provided inside buildings; hence, there is a need to visualize points-of-interest (POIs) that can describe these indoor service facilities on indoor maps. Over the last few years, indoor mapping has been a rapidly developing area, with the emergence of many forms of indoor representation. In the design of indoor map applications, cartographical methodologies such as generalization and symbolization can make important contributions. In this study, a self-adaptive method is applied for the design of a multi-scale and personalized indoor map. Based on methods of map generalization and multi-scale representation, we adopt a scale-adaptive strategy to visualize the building structure and POI data on indoor maps. At smaller map scales, the general floor distribution and functional partitioning of each floor are represented, while the POI data are visualized by simple symbols. At larger map scales, the detailed room distribution is displayed, and the service information of the POIs is described by detailed symbols. Different strategies are used for the generalization of the background building structure and the foreground POI data to ensure that both can satisfy real-time performance requirements. In addition, for better personalization, different POI data, symbols or color schemes are shown to users in different age groups, with different genders or with different purposes for using the map. Because this indoor map is adaptive to both the scale and the user, each map scale can provide different map users with decision support from different perspectives.
Yi Xiao; Tinghua Ai; Min Yang; Xiang Zhang. A Multi-Scale Representation of Point-of-Interest (POI) Features in Indoor Map Visualization. ISPRS International Journal of Geo-Information 2020, 9, 239 .
AMA StyleYi Xiao, Tinghua Ai, Min Yang, Xiang Zhang. A Multi-Scale Representation of Point-of-Interest (POI) Features in Indoor Map Visualization. ISPRS International Journal of Geo-Information. 2020; 9 (4):239.
Chicago/Turabian StyleYi Xiao; Tinghua Ai; Min Yang; Xiang Zhang. 2020. "A Multi-Scale Representation of Point-of-Interest (POI) Features in Indoor Map Visualization." ISPRS International Journal of Geo-Information 9, no. 4: 239.
The shrimp-farming area and shrimp yield are continuously changing in the southwestern coastal districts of Bangladesh. The three southwestern coastal districts, Bagerhat, Satkhira, and Khulna, along with Rampal, a subdistrict of Bagerhat, contribute 75% of the total shrimp yield of Bangladesh. However, the shrimp yield and farming area have declined in Bagerhat district, and the cause of this decline is uncertain. In this research, the differences in the shrimp yield were quantified using a shrimp yield dataset (SYD) and k-means classification. A supervised image classification approach was applied to quantify the spatiotemporal changes and identify the influencing factors behind the declining shrimp-farming area and yield in Rampal, Bagerhat district, using Landsat satellite archives. K-means classification reveals that, between 2015 and 2017, the shrimp yield in Bagerhat district declined significantly compared to Satkhira and Khulna. The satellite-based monitoring results affirm that the shrimp-farming area of Rampal also decreased rapidly, from 21.82% in 2013 to 6.52% in 2018. This research estimates that approximately 70% of the shrimp-farming area was lost in Rampal since December 2013. Hence, the findings of this research might motivate the responsible bodies to declare the shrimp-farming coastal area as a “shrimp zone” and implement an active policy to protect the vulnerable shrimp-farming industry and shrimp farmers, considering it is the second-largest export earning source in Bangladesh after ready-made garments.
Fazlul Karim; Xiang Zhang; Ru Li. Dynamics of Shrimp Farming in the Southwestern Coastal Districts of Bangladesh Using a Shrimp Yield Dataset (SYD) and Landsat Satellite Archives. Sustainability 2019, 11, 4635 .
AMA StyleFazlul Karim, Xiang Zhang, Ru Li. Dynamics of Shrimp Farming in the Southwestern Coastal Districts of Bangladesh Using a Shrimp Yield Dataset (SYD) and Landsat Satellite Archives. Sustainability. 2019; 11 (17):4635.
Chicago/Turabian StyleFazlul Karim; Xiang Zhang; Ru Li. 2019. "Dynamics of Shrimp Farming in the Southwestern Coastal Districts of Bangladesh Using a Shrimp Yield Dataset (SYD) and Landsat Satellite Archives." Sustainability 11, no. 17: 4635.
Crowd-sourced geographic information is becoming increasingly available, providing diverse and timely sources for updating existing spatial databases to facilitate urban studies, geoinformatics, and real estate practices. However, the discrepancies between heterogeneous datasets present challenges for automated change detection. In this paper, we identify important measurable factors to account for issues like boundary mismatch, large offset, and discrepancies in the levels of detail between the more current and to-be-updated datasets. These factors are organized into rule sets that include data matching, merge of the many-to-many correspondence, controlled displacement, shape similarity, morphology of difference parts, and the building pattern constraint. We tested our approach against OpenStreetMap and a Dutch topographic dataset (TOP10NL). By removing or adding some components, the results show that our approach (accuracy = 0.90) significantly outperformed a basic geometric method (0.77), commonly used in previous studies, implying a more reliable change detection in realistic update scenarios. We further found that distinguishing between small and large buildings was a useful heuristic in creating the rules.
Xiaodong Zhou; Zhe Chen; Xiang Zhang; Tinghua Ai. Change Detection for Building Footprints with Different Levels of Detail Using Combined Shape and Pattern Analysis. ISPRS International Journal of Geo-Information 2018, 7, 406 .
AMA StyleXiaodong Zhou, Zhe Chen, Xiang Zhang, Tinghua Ai. Change Detection for Building Footprints with Different Levels of Detail Using Combined Shape and Pattern Analysis. ISPRS International Journal of Geo-Information. 2018; 7 (10):406.
Chicago/Turabian StyleXiaodong Zhou; Zhe Chen; Xiang Zhang; Tinghua Ai. 2018. "Change Detection for Building Footprints with Different Levels of Detail Using Combined Shape and Pattern Analysis." ISPRS International Journal of Geo-Information 7, no. 10: 406.
Knowledge or rule-based approaches are needed for quality assessment and assurance in professional or crowdsourced geographic data. Nevertheless, many types of geographic knowledge are statistical in nature and are therefore difficult to derive rules that are meaningful for this purpose. The rules of continuity and symmetry considered in this paper can be thought of as two concrete forms of the first law of geography, which may be used to formulate quality measures at the individual level without referring to ground truth. It is not clear, however, how much the rules can be faithful. Hence, the main objective is to test if the rules are consistent with street network data over the world. Specifically, for the rule of continuity we identify natural streets that connect smoothly in a network, and measure the spatial order of information (e.g. names, highway level, speed, etc.) along the streets. The measure is based on spatial auto-correlation indicators adapted for one dimension. For the rule of symmetry, we device an algorithm that recognize parallel road pairs (e.g. dual carriageways), and examine to what extent attributes in the pairs are identical. The two rules are tested against 28 cities selected from OpenStreetMap data worldwide; two professional data sets are used to show more insights. We found that the rules are consistent with street networks from a wide range of cities of different characteristics, and also noted cases with varying degrees of agreement. As a side-effect, we discussed possible limitations of the autocorrelation indicators used, where cautions are needed when interpreting the results. In addition, we present techniques that performed the tests automatically, which can be applied to new data to further verify (or falsify) our findings, or extended as quality assurance tools to detect data items that do not satisfy the rules and to suggest possible corrections according to the rules.
Xiang Zhang; Weijun Yin; Shouqian Huang; Jianwei Yu; Zhongheng Wu; Tinghua Ai. On the rules of continuity and symmetry for the data quality of street networks. PLOS ONE 2018, 13, e0200334 .
AMA StyleXiang Zhang, Weijun Yin, Shouqian Huang, Jianwei Yu, Zhongheng Wu, Tinghua Ai. On the rules of continuity and symmetry for the data quality of street networks. PLOS ONE. 2018; 13 (7):e0200334.
Chicago/Turabian StyleXiang Zhang; Weijun Yin; Shouqian Huang; Jianwei Yu; Zhongheng Wu; Tinghua Ai. 2018. "On the rules of continuity and symmetry for the data quality of street networks." PLOS ONE 13, no. 7: e0200334.
Integrating updates from timely sources such as volunteered geographic information (VGI) into the spatial data maintained at official agencies is becoming a more demanding requirement but presents many challenges. This paper proposes an approach to addressing the technical challenge of propagating updates from timely sources (e.g. OpenStreetMap) to spatial data maintained at separate map scales. The main idea is to establish a multiple representation database (MRDB) for datasets at different scales and time to facilitate incremental update, where linkages between corresponding objects at different datasets are made explicit. First, two ways in which the timely sources can be integrated into official data for incremental update are discussed. To derive the linkages between different datasets, a data matching procedure based on computer vision is presented and fine-tuned to match data in different scale ranges. Furthermore, the generalization history used to produce smaller scale data from the larger ones in official data is inferred based on the linkages, and is then used to guide the update propagation. Finally, a framework for incremental generalization in MRDBs is proposed, where crucial issues like strategies for update propagation, cartographic generalization, and the so-called ‘chain reaction’ are addressed. The framework is implemented as a fully automated process where operators like simplification, enlargement, compression, displacement and typification are incorporated into the incremental update process. By testing the framework against real world data sets (i.e. OpenStreetMap and official data at 1:10k, 1:50k and 1:100k), we show that the updates are integrated consistently into existing data in terms of spatial relations and cartographic quality. Our work suggests that making use of timely sources by official mapping agencies and companies in a continuous or event-driven data update is technically feasible, with further improvement and extensions discussed.
Xiang Zhang; Weijun Yin; Min Yang; Tinghua Ai; Jantien Stoter. Updating authoritative spatial data from timely sources: A multiple representation approach. International Journal of Applied Earth Observation and Geoinformation 2018, 72, 42 -56.
AMA StyleXiang Zhang, Weijun Yin, Min Yang, Tinghua Ai, Jantien Stoter. Updating authoritative spatial data from timely sources: A multiple representation approach. International Journal of Applied Earth Observation and Geoinformation. 2018; 72 ():42-56.
Chicago/Turabian StyleXiang Zhang; Weijun Yin; Min Yang; Tinghua Ai; Jantien Stoter. 2018. "Updating authoritative spatial data from timely sources: A multiple representation approach." International Journal of Applied Earth Observation and Geoinformation 72, no. : 42-56.
This study proposes a template matching simplification method from the perspective of shape cognition based on the typical template characteristics of building distributions and representations. The method first formulates a series of templates to abstract the building shape by generalizing their polygons and analyzing their symbolic meanings, then conducts the simplification by searching and matching the most similar template that can be used later to replace the original building. On the premise of satisfying the individual geometric accuracy on a smaller scale, the proposed method can enhance the impression of well-known landmarks and reflect the pattern in mapping areas by the symbolic template. The turning function that describes shape by measuring the changes of the tangent-angle as a function of the arc-length is employed to obtain the similar distance between buildings and template polygons, and the least squares model is used to control the geometry matching of the candidate template. Experiments on real datasets are carried out to assess the usefulness of this method and compare it with two existing methods. The experiments suggest that our method can preserve the main structure of building shapes and geometric accuracy.
Xiongfeng Yan; Tinghua Ai; Xiang Zhang. Template Matching and Simplification Method for Building Features Based on Shape Cognition. ISPRS International Journal of Geo-Information 2017, 6, 250 .
AMA StyleXiongfeng Yan, Tinghua Ai, Xiang Zhang. Template Matching and Simplification Method for Building Features Based on Shape Cognition. ISPRS International Journal of Geo-Information. 2017; 6 (8):250.
Chicago/Turabian StyleXiongfeng Yan; Tinghua Ai; Xiang Zhang. 2017. "Template Matching and Simplification Method for Building Features Based on Shape Cognition." ISPRS International Journal of Geo-Information 6, no. 8: 250.
In recent years, main cities in China have been suffering from hazy weather, which is gaining great attention among the public, government managers and researchers in different areas. Many studies have been conducted on the topic of urban air quality to reveal different aspects of the air quality problem in China. This paper focuses on the visualization problem of the big air quality monitoring data of all main cities on a nationwide scale. To achieve the intuitive visualization of this data set, this study develops two novel visualization tools for multi-granularity time series visualization (timezoom.js) and a dynamic symbol declutter map mashup layer for thematic mapping (symadpative.js). With the two invented tools, we develops an interactive web map visualization application of urban air quality data of all main cities in China. This application shows us significant air pollution findings at the nationwide scale. These results give us clues for further studies on air pollutant characteristics, forecasting and control in China. As the tools are invented for general visualization purposes of geo-referenced time series data, they can be applied to other environmental monitoring data (temperature, precipitation, etc.) through some configurations.
Wei Lu; Tinghua Ai; Xiang Zhang; Yakun He. An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China. Atmosphere 2017, 8, 148 .
AMA StyleWei Lu, Tinghua Ai, Xiang Zhang, Yakun He. An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China. Atmosphere. 2017; 8 (12):148.
Chicago/Turabian StyleWei Lu; Tinghua Ai; Xiang Zhang; Yakun He. 2017. "An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China." Atmosphere 8, no. 12: 148.
Ontology-driven concept inference has the merit of high flexibility and transparency. Users can composite and reuse atomic primitive concepts and relationship to interpret complex geographical concept without the need to retouch or even know the technical details. The major issue that we are focusing on is the implicit geometry problem. That is, the geometries corresponding to some primitive concept defining the complex geographic concept are missing or not fully represented in a spatial database, making it impossible to inferring the high-level semantics of the objects. This paper combines terminological/assertional inference (for general logic reasoning) and spatial operations (for making implicit geometries explicit), therefore enabling an ontology-driven inference of complex concepts that can handle cases where some concept has no explicit geometries. In the end, the concept of peninsula is used to demonstrate the proposed methodology.
Xiang Zhang; Tinghua Ai; Jantien Stoter. Inferring Complex Geographical Concepts with Implicit Geometries Using Ontologies: A Case of Peninsulas. Lecture Notes in Geoinformation and Cartography 2016, 35, 21 -36.
AMA StyleXiang Zhang, Tinghua Ai, Jantien Stoter. Inferring Complex Geographical Concepts with Implicit Geometries Using Ontologies: A Case of Peninsulas. Lecture Notes in Geoinformation and Cartography. 2016; 35 ():21-36.
Chicago/Turabian StyleXiang Zhang; Tinghua Ai; Jantien Stoter. 2016. "Inferring Complex Geographical Concepts with Implicit Geometries Using Ontologies: A Case of Peninsulas." Lecture Notes in Geoinformation and Cartography 35, no. : 21-36.
OpenStreetMap (OSM) is mostly a good map for viewers to look at but it lacks of sufficient quality in certain applications like navigation. Quality issues are usually related to how roads are ‘drawn’ (modeled) by OSM contributors. First of all, this paper identifies several issues in tagging and modeling OSM road network by case studies, and also gives suggestions for contributors and routing service providers. As a key contribution, this paper proposes a methodology to evaluate OSM roads that does not rely on reference data or ground truth. The evaluation aims not only to identify errors in OSM data, but also to give more intelligent suggestions based on the information available in the spatial context of the problematic data. More specifically, named roads are recognized based on the concept of “stroke”. Missing or incorrect names can be found by outlier detection within the scope of the named roads. Such an idea can be widely applied to detect inconsistent tags and provide intelligent suggestions for data correction.
Xiang Zhang; Tinghua Ai. How to Model Roads in OpenStreetMap? A Method for Evaluating the Fitness-for-Use of the Network for Navigation. Advances in Geographic Information Science 2015, 143 -162.
AMA StyleXiang Zhang, Tinghua Ai. How to Model Roads in OpenStreetMap? A Method for Evaluating the Fitness-for-Use of the Network for Navigation. Advances in Geographic Information Science. 2015; ():143-162.
Chicago/Turabian StyleXiang Zhang; Tinghua Ai. 2015. "How to Model Roads in OpenStreetMap? A Method for Evaluating the Fitness-for-Use of the Network for Navigation." Advances in Geographic Information Science , no. : 143-162.
To meet the requirements of multi-scale mapping in maritime applications, marine charts need to be produced at various levels of detail (LOD) using map generalization. As a prominent geographic feature, the coastline has to be generalized considering the geomorphologic characteristics rather than from a pure geometric perspective. Morphologic and domain-specific constraints (e.g., safety) should be incorporated in designing a coastline generalization algorithm. Motivated by the generalization of ria coastlines, this article proposes a simplification algorithm that is specific to coastlines. An analysis of ria coasts results in several morphologic constraints that have to be satisfied in coastline generalization, such as the dendritic pattern of estuaries. To satisfy these constraints, a hierarchical estuary tree model is first established by Delaunay triangulation, which helps to represent the dendritic pattern of ria coastlines. Minor estuaries are then deleted to achieve a reasonable coastline simplification. To imitate manual generalization, an indicator is designed to calculate the importance of estuaries in a context dependent manner. By comparing with a well-known bend simply algorithm, we show that the presented method can maintain dendritic pattern of coastline and is free from self-intersection and also granted for navigation safety. This article also demonstrates that the proposed approach is applicable to coastlines in general.
Tinghua Ai; Qi Zhou; Xiang Zhang; Yafeng Huang; Mengjie Zhou. A Simplification of Ria Coastline with Geomorphologic Characteristics Preserved. Marine Geodesy 2014, 37, 167 -186.
AMA StyleTinghua Ai, Qi Zhou, Xiang Zhang, Yafeng Huang, Mengjie Zhou. A Simplification of Ria Coastline with Geomorphologic Characteristics Preserved. Marine Geodesy. 2014; 37 (2):167-186.
Chicago/Turabian StyleTinghua Ai; Qi Zhou; Xiang Zhang; Yafeng Huang; Mengjie Zhou. 2014. "A Simplification of Ria Coastline with Geomorphologic Characteristics Preserved." Marine Geodesy 37, no. 2: 167-186.
This chapter presents the context, the issues and the research associated with the evaluation of map generalisation output as well as of map readability. Two main approaches of evaluation are described, i.e. visual and quantitative evaluation. Visual evaluation is subjective, qualitative, and time-consuming, while it is argued that quantitative evaluation is only appropriate for assessing specific aspects. Since automated evaluation is becoming very important in the field of automated generalisation, this chapter further explores the topic of automated evaluation. The previous frameworks for automated generalisation are reviewed and the three main components of automated evaluation are explained. Related to automated evaluation of generalisation output are formulas to automatically evaluate map readability. These are also discussed. This chapter ends with three case studies. The first Case study identifies and evaluates generalised building patterns. It demonstrates the three-step approach of data enrichment, data matching and constraint evaluation. The second Case study deals with formulas to automatically evaluate map readability and the third Case study carries out a comprehensive evaluation demonstrating the main aspects described in this chapter. Both visual and quantitative evaluation are applied of which the last one includes the three main components of automated evaluation. The chapter closes with conclusions and highlights research issues in evaluation.
Jantien Stoter; Xiang Zhang; Hanna Stigmar; Lars Harrie. Evaluation in Generalisation. Lecture Notes in Geoinformation and Cartography 2014, 259 -297.
AMA StyleJantien Stoter, Xiang Zhang, Hanna Stigmar, Lars Harrie. Evaluation in Generalisation. Lecture Notes in Geoinformation and Cartography. 2014; ():259-297.
Chicago/Turabian StyleJantien Stoter; Xiang Zhang; Hanna Stigmar; Lars Harrie. 2014. "Evaluation in Generalisation." Lecture Notes in Geoinformation and Cartography , no. : 259-297.
This paper presents a first-order representation to formalize cartographic constraints for automated quality evaluation of multi-scale data. Formalizing constraints for cartographic applications is a challenging task. It requires precise definition of entities, spatial and semantic relationships for individuals, groups and classes of objects, and their (intra-/inter-scale) relationships. Also constraints defining the visual presentation of the same entities can be different depending on the scale and context. This paper categorizes and formalizes different types of information needed for the quality evaluation, based on which cartographic constraints are formalized. The formalism is demonstrated by applying it to group features such as networks and alignments, and finally to constraints of different levels of complexity. We show the potential of the proposed formalism and discuss possibilities for further development.
Xiang Zhang; Tinghua Ai; Jantien Stoter; Jingzhong Li. Towards Cartographic Constraint Formalization for Quality Evaluation. Lecture Notes in Geoinformation and Cartography 2013, 89 -101.
AMA StyleXiang Zhang, Tinghua Ai, Jantien Stoter, Jingzhong Li. Towards Cartographic Constraint Formalization for Quality Evaluation. Lecture Notes in Geoinformation and Cartography. 2013; ():89-101.
Chicago/Turabian StyleXiang Zhang; Tinghua Ai; Jantien Stoter; Jingzhong Li. 2013. "Towards Cartographic Constraint Formalization for Quality Evaluation." Lecture Notes in Geoinformation and Cartography , no. : 89-101.
Evaluation is a key step to examine the quality of generalized maps with respect to map requirements. Map generalization facilitates the recognition of pattern generating processes by preserving and highlighting the patterns at smaller scales. This article focuses specifically on the evaluation of building patterns in topographic maps that are generalized from large to mid scales. Currently, there is a lack of knowledge and functionality on automatically evaluating how these patterns are generalized. The issues of the evaluation range from missing formal map requirements on building alignments to missing automated evaluation techniques. This article firstly analyses the requirements (constraints) related to the generalization of building alignments. Then, it focuses on three more specific constraints, i.e. on existence, orientation of alignments and spatial distribution of composing buildings. Later, a three-step approach is proposed to (1) recognize and (2) match alignments from source and generalized datasets and (3) evaluate building alignments in generalized datasets. Besides, many-to-many and partial matching between initial and target alignments is a side effect of generalization, which reduces the reliability of the evaluation results. This article introduces a confidence indicator to document the reliability and to inform intended users (e.g. cartographers) and/or systems about the reliability of evaluation decisions. The effectiveness of our approach is demonstrated by evaluating the alignments in both interactively (manually) generalized maps and automated generalized maps. Finally, we discuss how our approach can be used to control automated generalization and identify further improvements.
Xiang Zhang; Jantien Stoter; Tinghua Ai; Menno-Jan Kraak; Martien Molenaar. Automated evaluation of building alignments in generalized maps. International Journal of Geographical Information Science 2013, 27, 1550 -1571.
AMA StyleXiang Zhang, Jantien Stoter, Tinghua Ai, Menno-Jan Kraak, Martien Molenaar. Automated evaluation of building alignments in generalized maps. International Journal of Geographical Information Science. 2013; 27 (8):1550-1571.
Chicago/Turabian StyleXiang Zhang; Jantien Stoter; Tinghua Ai; Menno-Jan Kraak; Martien Molenaar. 2013. "Automated evaluation of building alignments in generalized maps." International Journal of Geographical Information Science 27, no. 8: 1550-1571.